Auto-Regressive Integrated Moving Average Model (ARIMA): conceptual and methodological aspects and applicability in infant mortality

Silva, Aline Beatriz dos Santos; Araújo, Ana Catarina de Melo; Frias, Paulo Germano de; Vilela, Mirella Bezerra Rodrigues; Bonfim, Cristine Vieira do

doi:10.1590/1806-93042021000200016

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SPECIAL ARTICLES • Instituto de Medicina Integral Prof. Fernando Figueira 21 (2) • Apr-Jun 2021 • https://doi.org/10.1590/1806-93042021000200016 copy

Auto-Regressive Integrated Moving Average Model (ARIMA): conceptual and methodological aspects and applicability in infant mortality

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

This reflective theoretical article, aims to discuss conceptual and methodological aspects about the applications of time series modeling, in particular, the Integrated Auto-regressive Moving Average model and its applicability in infant mortality. This modeling makes it possible to predict future values using past data, outlining and estimating possible scenarios of the health event, highlighting its magnitude. Due to the persistence of infant mortality as a public health problem, the applicability of this method is useful in the timely and systematic management of child health indicators, in addition to being a method with low operating cost, which in contexts of cost reduction in public healthcare services, becomes a potential management tool. However, there are still gaps in the use of statistical methods in the decision-making and policy-making process in public healthcare, such as the modeling in question. These are methodological (robust statistics), institutional (outdated information systems) and cultural obstacles (devaluation of the data produced, mainly at the local level).

Key words
Time series studies; Infant mortality; Public health policy

Title	Authors (Year of publication)	Applicability of the method
Change of Outcomes in Pediatric Intestinal Failure: Use of Time-Series Analysis to assess the evolution of an Intestinal Rehabilitation Program	Oliveiraet al.²⁵25 Oliveira C, Silva NT, Stanojevic S, Avitzur Y, Bayoumi AM, Ungar WJ, Hoch JS, Wales PW. Change of Outcomes in Pediatric Intestinal Failure: Use of Time-Series Analysis to assess the evolution of an Intestinal Rehabilitation Program. J Am Coll Surg. 2016; 222 (6): 1180-8.(2016)	The study evidenced the versatility of the ARIMA method, expanding its scope of application in the clinic. The efficacy of the treatment options in the improvement of the clinical status of neonatal or infantile intestinal failure was assessed, showing the downward trend in the primary outcome (mortality).
Post Millennium Development Goals Prospect on Child Mortality in India: An Analysis Using Autoregressive Integrated Moving Averages (ARIMA) Model	De et al.¹⁵15 De P, Sahu D, Pandey A, Gulati BK, Chandhiok N, Shukla AK, Mohan P, Mitra RG. Post Millennium Development Goals Prospect on Child Mortality in India: An Analysis Using Autoregressive Integrated Moving Averages (ARIMA) Model. Health. 2016; 8 (15): 1845-72. (2016)	The ARIMA modeling was used to support the monitoring of the Sustainable Development Goals in India and forecast the health care actions to be given priority in order to achieve the respective goals, as well as an essential tool for formulating an overall national health planning.
Predicting infant mortality in India using time series models	Singh and Singh²⁶26 Singh MP, Singh RD. Predicting infant mortality in India using time series models. Int J Statistics Appl Mathematics. 2018; 3(5): 33-42. (2018)	The method was applied to forecast the child mortality rate in some states of India. It allowed the comparison between the respective historical series and the forecasts.
Trend of Neonatal Mortality in Nigeria from 1990 to 2017 using Time Series Analysis	Usman et al.¹⁴14 Usman A, Sulaiman MA, Abubakar I. Trend of Neonatal Mortality in Nigeria from 1990 to 2017 using Time Series Analysis. J. Appl. Sci. Environ. Manage. 2019; 23 (5): 865- 9. (2019)	The ARIMA modeling was used to investigate the trend of incidence of neonatal mortality, making the 20-year forecast. A consistent decline in the neonatal mortality rate is evidenced, in addition to the fact that the local neonatal health policy is operational and committed to reducing the incidence of neonatal deaths.
Trends and future of maternal and child health in Bangladesh	Rajia et al.²²22 Rajia S, Sabiruzzaman M, Islam MK, Hossain MG, Lestrel PE. Trends and future of maternal and child health in Bangladesh. PLoS One. 2019; 14 (3): e0211875. (2019)	The method enabled the analysis of the trend of the maternal and child health indicators. With the scenario forecasted for the rates, it is characterized as a potential tool for supporting the decision-making of local management in monitoring and the implications of public policies to achieve the goals proposed in the 2030 Agenda.
A mortalidade infantil no estado de São Paulo: uma previsão da taxa por meio da modelagem SARIMA	Chaib²⁷27 Chaib DC. A mortalidade infantil no estado de São Paulo: uma previsão da taxa por meio da modelagem SARIMA. Rev Econ UEG]. 2019; 15 (1): 43-52. (20 1 9)	The historical series was used to describe the evolution of the child mortality rate over time (1996-2016). The ARIMA method applied enabled evidencing the seasonal behavior of child mortality, as it has drops in specific periods, hence identifying a SARIMA model. The forecast evidences a downward trend for the rate.
Forecasting Indian infant mortality rate: An application of autoregressive integrated moving average model	Mishra et al.³3 Mishra AK, Sahanaa C, Manikandan M. Forecasting Indian infant mortality rate: An application of autoregressive integrated moving average model. J Family Community Med. 2019; 26 (2): 123-6.(2019)	The ARIMA modeling allowed defining an overview for a future scenario of child mortality. The forecast was for the nine-year period (2017-2025), with a downward trend. The study highlights one potential of the method: the reliability of the forecast when it estimates the period of the sample using available data. It evidences that it is a statistical tool of great value in health care, supporting the planning of interventions.
Modeling and Forecasting Infant Deaths in Zimbabwe using ARIMA Models	Nyoni and Nyoni⁵5 Nyoni SP, Nyoni T. Modeling and forecasting Infant deaths in Zimbabwe using ARIMA Models. JournalNX - A Multidisciplinary Peer Reviewed Journal. 2020; 6 (7): 142- 51.(2020)	The model was applied to forecast the number of child deaths in a country under peripheral capitalism with a high mortality rate. Having such information would bring gains more effectively to the local health intervention programs.

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[1] Author’s contribution

Silva ABS, Frias PG, Vilela MBR, Bonfim CV, and Araújo ACM contributed to all stages of the preparation of the paper: conception, outlining, writing, and approval of the final version of the paper.